Image Retrieval Model Analysis of Digital Library Based on Texture Characteristics

A new document image retrieval algorithm is proposed in view of the inefficient retrieval of information resources in a digital library. First of all, in order to accurately characterize the texture and enhance the ability of image differentiation, this paper proposes the statistical feature method...

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Autor principal:	Yu Zhao
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Physics QC1-999
Acceso en línea:	https://doaj.org/article/eac7488193674604a0590417ad42f353
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spelling	oai:doaj.org-article:eac7488193674604a0590417ad42f3532021-11-08T02:37:00ZImage Retrieval Model Analysis of Digital Library Based on Texture Characteristics1687-913910.1155/2021/6014946https://doaj.org/article/eac7488193674604a0590417ad42f3532021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/6014946https://doaj.org/toc/1687-9139A new document image retrieval algorithm is proposed in view of the inefficient retrieval of information resources in a digital library. First of all, in order to accurately characterize the texture and enhance the ability of image differentiation, this paper proposes the statistical feature method of the double-tree complex wavelet. Secondly, according to the statistical characteristic method, combined with the visual characteristics of the human eye, the edge information in the document image is extracted. On this basis, we construct the meaningful texture features and use texture features to define the characteristic descriptors of document images. Taking the descriptor as the clue, the content characteristics of the document image are combined organically, and appropriate similarity measurement criteria are used for efficient retrieval. Experimental results show that the algorithm not only has high retrieval efficiency but also reduces the complexity of the traditional document image retrieval algorithm.Yu ZhaoHindawi LimitedarticlePhysicsQC1-999ENAdvances in Mathematical Physics, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Physics QC1-999
spellingShingle	Physics QC1-999 Yu Zhao Image Retrieval Model Analysis of Digital Library Based on Texture Characteristics
description	A new document image retrieval algorithm is proposed in view of the inefficient retrieval of information resources in a digital library. First of all, in order to accurately characterize the texture and enhance the ability of image differentiation, this paper proposes the statistical feature method of the double-tree complex wavelet. Secondly, according to the statistical characteristic method, combined with the visual characteristics of the human eye, the edge information in the document image is extracted. On this basis, we construct the meaningful texture features and use texture features to define the characteristic descriptors of document images. Taking the descriptor as the clue, the content characteristics of the document image are combined organically, and appropriate similarity measurement criteria are used for efficient retrieval. Experimental results show that the algorithm not only has high retrieval efficiency but also reduces the complexity of the traditional document image retrieval algorithm.
format	article
author	Yu Zhao
author_facet	Yu Zhao
author_sort	Yu Zhao
title	Image Retrieval Model Analysis of Digital Library Based on Texture Characteristics
title_short	Image Retrieval Model Analysis of Digital Library Based on Texture Characteristics
title_full	Image Retrieval Model Analysis of Digital Library Based on Texture Characteristics
title_fullStr	Image Retrieval Model Analysis of Digital Library Based on Texture Characteristics
title_full_unstemmed	Image Retrieval Model Analysis of Digital Library Based on Texture Characteristics
title_sort	image retrieval model analysis of digital library based on texture characteristics
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/eac7488193674604a0590417ad42f353
work_keys_str_mv	AT yuzhao imageretrievalmodelanalysisofdigitallibrarybasedontexturecharacteristics
_version_	1718443051765989376

Image Retrieval Model Analysis of Digital Library Based on Texture Characteristics

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